Users of distributed computing environments, message-oriented middleware environments, and other computer processes wherein information is exchanged between communicating entities continue to demand higher performance without sacrificing process reliability. For example, a user of a distributed computing environment, wherein a client sends out workload and expects results, may require a 5 ms or less round trip workload latency in an environment with thousands of compute nodes and clients. In the traditional store-and-forward approach, a server receives the client's workload and forwards the workload to compute nodes in the distributed computing environment. But before forwarding the workload, the server stores the workload in nonvolatile memory and sends an acknowledgement to the client. User performance requirements, however, are often unattainable with the traditional store-and-forward approach because the total system performance can never exceed the maximum performance of the storage operation. Because the storage operation is often the lowest performing operation in the system, a new approach is needed to meet higher performance and reliability requirements.